We comprehensively evaluate our method on the five public challenging datasets: MIT300 [1]}, MIT1003 [2]}, TORONTO [3]}, PASCAL-S [4]} and DUT-OMRON [5]}, where the proposed attention model produces more accurate saliency maps than state-of-the-arts. Meanwhile, it achieves a frame rate of 10fps on a GPU. Thus it is a practical attention prediction model in terms of both speed and accuracy. To summarize, the main contributions are three-fold:
